is a multi-drug resistant opportunistic pathogen, which causes respiratory and urinary tract infections. Its prevalence increases gradually in the clinical setup. Carbapenems (beta-lactam) are most ...effective antibiotics till now against
, but the development of resistance against it may lead to high mortality. Therefore, it is of utmost importance to develop an alternative drug against
. In the present study, we have synthesized ZnO nanoparticle (ZnO-NP) and characterized by X-ray diffraction, Fourier transform infrared (FTIR) spectroscopy and UV-Visible spectroscopy. Prepared ZnO-NPs have the size of 30 nm and have different characteristics of ZnO-NPs. Growth kinetics and disk diffusion assay showed that ZnO-NP demonstrated good antibacterial activity against carbapenem resistant
. We have also investigated the mechanism of action of ZnO-NPs on the carbapenem resistant strain of
. The proposed mechanism of action of ZnO involves the production of reactive oxygen species, which elevates membrane lipid peroxidation that causes membrane leakage of reducing sugars, DNA, proteins, and reduces cell viability. These results demonstrate that ZnO-NP could be developed as alternative therapeutics against
.
Aims and Objectives: This study aimed to compare the vitamin D levels between chronic obstructive pulmonary disease (COPD) patients and healthy controls and to describe the correlation between ...vitamin D levels and lung functions. Methods: Fifty COPD patients (cases) and 30 healthy volunteers (controls) were recruited and their serum vitamin D level was measured together with lung function (forced vital capacity and forced expiratory volume in 1 s FEV1) by spirometry. vitamin D was categorized as ≤20 nmol/l: deficient, 21-50 nmol/l: inadequate, and ≥51 nmol/l as sufficient. Results: In this case-control cross-sectional study, lower vitamin D levels were associated with lower lung function in both cases as well as controls, the effect being more pronounced in cases. Mean FEV1 at vitamin D ≤20 nmol/l (0.98 ± 0.40 vs. controls 1.93 ± 0.24 with P = 0.006), mean FEV1 at vitamin D 21-50 nmol/l (1.55 ± 0.54 vs. 2.20 ± 0.31 with P = 0.000), and mean FEV1 at vitamin D ≥51 nmol/l (2.06 ± 0.54 vs. 2.20 ± 0.31 with P = 0.002). Moreover, the severity of predicted postbronchodilator FEV1% was also much lower among COPD cohort versus healthy volunteers (mean FEV1%: cases 47.88 ± 14.22 vs. controls 58.76 ± 15.05 with P = 0.002). Conclusions: Importantly, lung function in both the groups was affected by decreased vitamin D level; decrease in FEV1 was more pronounced among COPD patients compared to controls showing more expiratory airflow limitation. Vitamin D levels are associated with changes in lung function in cases of COPD as well as healthy controls. Larger studies to confirm the association in Indian context are required and routine assessment of vitamin D may be undertaken to obviate the effects of low vitmain D level on lung function.
Automatic Speech Recognition (ASR) has become one of the major research areas over the past decade and gained a lot of interest. Their system implementation, adaptation to different languages and ...robustness in the performance are still some of the major challenges. Hindi is one of the most widely spoken languages in the world but it is a complex and resource-constraint language. Thus, speech recognition and classification systems need to be developed for Hindi language to spread the technology and to explore more communication means. But due to its language complexity than other languages and lack of standard databases, it is quite challenging to develop such systems. Deep learning is extensively used in different research fields and has proven its prominence to a broader extent. In this paper, a seven-layer 1D-convolutional neural network HindiSpeech-Net has been proposed to recognise different speech samples of the Hindi language in the respective category. A large dataset of 2400 speech samples in the Hindi language is collected in ten different classes in real-world conditions which is further accompanied by signal filtering and augmentation to enhance the dataset for making a robust model and avoid overfitting. The collected dataset is divided into training, validation and test set which were evaluated in different performance parameters. The trained HindiSpeech-Net model achieved an accuracy of 92.92% on the test set. The proposed framework is computationally less expensive, works in real-time and is suitable for implementation in embedded systems.
The present results demonstrate the feasibility of friction stir processing to produce a microstructure amenable to high strain rate superplasticity in a commercial aluminum alloy. Optimum ...superplasticity was observed in a friction stir processed 7075 Al alloy at 1x10 exp -2 s exp -1 and 490 deg C.
In this work secondary ion mass spectroscopy was used to investigate the incorporation of oxygen, carbon, and hydrogen impurities in smooth N-face (0
0
0
1¯) and Ga-face (0
0
0
1) GaN films grown by ...metalorganic chemical vapor deposition. The smooth N-face films were obtained on vicinal sapphire substrates, of which the misorientations 2°, 4°, and 5° towards 1
01¯
0
Al
2
O
3
as well as 4° and 5° towards 1
1
2¯
0
Al
2
O
3
were explored. Results are presented for variations in temperature, pressure, V/III ratio, and Ga flow. Additionally, the incorporation of intentional dopants Si, for n-type doping, and Mg, for p-type doping were investigated. The misorientation angle and direction did not impact the impurity incorporation on the N-face. In comparison to the Ga-face, the N-face GaN films contained significantly higher concentrations of oxygen, however, demonstrated lower levels of carbon. Incorporation of Mg and Si dopants were found to be similar in N-face and Ga-face films. Additionally, significantly sharper Mg-doping profiles in N-face films in comparison to Ga-face films were observed.
This paper demonstrates the effect of incorporating Deep Neural Network techniques in speech recognition systems. Speech recognition through hybrid Deep Neural Networks on the Kaldi toolkit for the ...Punjabi language is implemented. Performance of the automatic speech recognition system drastically improves using DNN, and further Karel's DNN model gives better recognition performance as compared to Dan's DNN model. Out of MFCC and PLP features, the MFCC feature gives better results. The triphone model gives a lower word error rate than the monophone model, and 3-g gives a lower word error rate as compared to a 2-g model on the Kaldi toolkit for the continuous Punjabi speech recognition system.
•Laser Powder Bed Fusion of single tracks and thin walls at 100 μm layer thickness.•Process window identified in terms of energy density for stable single tracks.•Parametric investigation on track ...morphology, track geometry and wall geometry.•Analytical and regression models developed for track and wall geometry.•Geometrical variation from single track to thin walls investigated.
Laser Powder Bed Fusion (LPBF) is one of the advanced manufacturing technologies used for fabricating near net shaped components directly from CAD model data by selectively melting pre-placed layer of powder in layer by layer fashion. LPBF process is widely researched with layer thickness up to 60 µm and is now commercially deployed for many metallic materials. However, very limited literature is available in public domain for LPBF with layer thickness >60 µm as the process in this window has many challenges in geometry control and reproducibility due to inherent process instability. However, higher layer thickness with larger beam diameter can bring better productivity and shorter built time with limited compromise on minimum feature size. The present work focuses on a systematic parametric study on single track and thin wall fabrication using LPBF at layer thickness of 100 µm by varying laser power (150–450 W) and scan speed (0.02–0.08 m/s) using SS 316L powder. For the range of parameters under investigation, process window yielding stable tracks (regular and uniform) is obtained for energy density between 87.5 and 140 J/mm3. An analytical model for predicting the width of the track and a regression model for the depth of re-melted zone in the substrate subsurface and track area during single track fabrication is developed in terms of energy density. The average difference in predicted and experimental values for width and area of the track are 3.18% and 7.61%, respectively within the process window. Width of thin walls built at the same parameters is measured and the variation between width of thin wall and track is estimated in terms of energy density. The width of thin walls fabricated are observed to be larger than that of single track built at the same combinations of process parameters primarily due to preheating effect. For the range of parameters under investigation, the highest values of width of thin wall and its difference from corresponding width of track is observed at 112.5 J/mm3 in the process window. The study paves a way in understanding the effect of higher layer thickness on the geometry of LPBF built components.
In this paper, continuous Punjabi speech recognition model is presented using Kaldi toolkit. For speech recognition, the extraction of Mel frequency cepstral coefficients (MFCC) features and ...perceptual linear prediction (PLP) features were extracted from Punjabi continuous speech samples. The performance of automatic speech recognition (ASR) system for both monophone and triphone model i.e., tri1, tri2 and tri3 model using N-gram language model is reported. The performance of ASR system were computed in terms of word error rate (WER). A significant reduction in WER was observed using the tri phone model over mono phone model ASR .Also the performance of ASR using tri3 model is improved over tri2 model and the performance of tri2 model is improved over tri1 model ASR. Further, it was found that MFCC feature provides higher speech recognition accuracy than PLP features for continuous Punjabi speech.
Interactions among mutations within a protein have the potential to make molecular evolution contingent and irreversible, but the extent to which epistasis actually shaped historical evolutionary ...trajectories is unclear. To address this question, we experimentally measured how the fitness effects of historical sequence substitutions changed during the billion-year evolutionary history of the heat shock protein 90 (Hsp90) ATPase domain beginning from a deep eukaryotic ancestor to modern Saccharomyces cerevisiae. We found a pervasive influence of epistasis. Of 98 derived amino acid states that evolved along this lineage, about half compromise fitness when introduced into the reconstructed ancestral Hsp90. And the vast majority of ancestral states reduce fitness when introduced into the extant S. cerevisiae Hsp90. Overall, more than 75% of historical substitutions were contingent on permissive substitutions that rendered the derived state nondeleterious, became entrenched by subsequent restrictive substitutions that made the ancestral state deleterious, or both. This epistasis was primarily caused by specific interactions among sites rather than a general effect on the protein’s tolerance to mutation. Our results show that epistasis continually opened and closed windows of mutational opportunity over evolutionary timescales, producing histories and biological states that reflect the transient internal constraints imposed by the protein’s fleeting sequence states.
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